Optimizing metal part distortion in the material extrusion-thermal debinding-sintering process: An experimental and numerical study

The thermal debinding-sintering process plays an essential role in the context of material extrusion-based additive manufacturing (AM) for producing parts using metal injection molding (MIM). During thermal debinding, metal parts often experience material distortion and porosity, which negatively impacts their mechanical properties. Slowing down the debinding speed is a common approach to mitigate material distortion and porosity. However, this leads to a significant increase in the debinding time. In this study, we carried out debinding-sintering experiments to optimize the distortion and porosity in metal parts. These metal parts were manufactured utilizing bronze/polylactide (PLA) blend filaments and placed in crucibles of different sizes (small, medium, and large), with different heating rates and holding times. The results revealed that the small crucible yielded higher porosity levels in the metal parts, which could be reduced from 23% to 12% by extending both the heating and holding times. In contrast, the medium crucible managed to reduce porosity to approximately 15% without requiring an extension of the processing time. The large crucible, on the other hand, couldn't achieve further porosity reduction due to challenges in reaching the desired temperature. To gain a deeper insight into temperature distribution during the debinding process, we performed numerical simulations using the computational fluid dynamics (CFD) technique and obtained temperature profiles within the kiln using the three crucibles. Ultimately, we carried out standard mechanical tests on the resulting metal parts and evaluated the thermal debinding procedure under various conditions. The approach we employed, combining experiments and numerical simulations, demonstrated significant promise for enhancing the quality of metal parts in the thermal debinding-sintering process.

Coupled neutronic core and subchannel analysis of nanofluids in VVER-1000 type reactor

This study is aimed to perform the coupled thermal-hydraulic/neutronic analysis of nanofluids as the coolant in the hot fuel assembly of VVER-1000 reactor core. Water-based nanofluid containing various volume fractions of Al2O3 nanoparticle is analyzed. WIMS and CITATION codes are used for neutronic simulation of the reactor core, calculating neutron flux and thermal power distribution. In the thermal-hydraulic modeling, the porous media approach is used to analyze the thermal behavior of the reactor core and the subchannel analysis is used to calculate the hottest fuel assembly thermal-hydraulic parameters. The derived conservation equations for coolant and conduction heat transfer equation for fuel and clad are discretized by Finite volume method and solved numerically using visual FORTRAN program. Finally the analysis results for nanofluids and pure water are compared together. The achieved results show that at low concentration (0.1 percent volume fraction) alumina is the optimum nanoparticles for normal reactor operation.

Subchannel analysis of Al2O3 nanofluid as a coolant in VMHWR

The main objective of this study is to predict the thermal hydraulic behavior of nanofluids as the coolant in the fuel assembly of variable moderation high performance light water reactor (VMHWR). VMHWR is the new version of high performance light water reactor (HPLWR) conceptual design. Light water reactors at supercritical pressure (VMHWR, HPLWR), being currently under design, are the new generation of nuclear reactors. Water-based nanofluids containing various volume fractions of Al2O3 nanoparticles are analyzed. The conservation equations and conduction heat transfer equation for fuel and clad have been derived and discretized by the finite volume method. The transfer of mass, momentum and energy between adjacent subchannels are split into diversion crossflow and turbulent mixing components. The governed non linear algebraic equations are solved by using analytical iteration methods. Finally the nanofluid analysis results are compared with the pure water results.